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Designing and in vitro testing of a novel patient-specific total knee prosthesis using the probabilistic approach

  • İsmail H. Korkmaz ORCID logo EMAIL logo , İrfan Kaymaz , Ömer S. Yıldırım , Fahri Murat and Halim Kovacı
Published/Copyright: May 9, 2022
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Biomedical Engineering / Biomedizinische Technik
From the journal Biomedical Engineering / Biomedizinische Technik Volume 67 Issue 4

Abstract

In order to prevent failure as well as ensure comfort, patient-specific modelling for prostheses has been gaining interest. However, deterministic analyses have been widely used in the design process without considering any variation/uncertainties related to the design parameters of such prostheses. Therefore, this study aims to compare the performance of patient-specific anatomic Total Knee Arthroplasty (TKA) with off-the-shelf TKA. In the patient-specific model, the femoral condyle curves were considered in the femoral component’s inner and outer surface design. The tibial component was designed to completely cover the tibia cutting surface. In vitro experiments were conducted to compare these two models in terms of loosening of the components. A probabilistic approach based on the finite element method was also used to compute the probability of failure of both models. According to the deterministic analysis results, 103.10 and 21.67 MPa von Mises stress values were obtained for the femoral component and cement in the anatomical model, while these values were 175.86 and 25.76 MPa, respectively, for the conventional model. In order to predict loosening damage due to local osteolysis or stress shield, it was determined that the deformation values in the examined cement structures were 15% lower in the anatomical model. According to probabilistic analysis results, it was observed that the probability of encountering an extreme value for the anatomical model is far less than that of the conventional model. This indicates that the anatomical model is safer than the conventional model, considering the failure scenarios in this study.

Keywords: experimental validation; finite element analysis; probability-based design; total knee arthroplasty
Corresponding author: İsmail H. Korkmaz, Department of Mechanical Engineering, Faculty of Engineering and Architecture, Erzurum Technical University, Erzurum, Turkey 25050, E-mail:

Funding source: Scientific and Technological Research Council of Turkey (TÜBİTAK)

Award Identifier / Grant number: 114M899

Acknowledgment

The authors would like to thank TÜBİTAK for its financial support in conducting this study.

  1. Research funding: This work was supported by funded Scientific and Technological Research Council of Turkey (TÜBİTAK), (Grant No. 114M899).

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent is not applicable.

  5. Ethical approval: The conducted research is not related to either human or animal use.

References

1. Ezzet, KA, Hermida, JC, Steklov, N, D′Lima, DD. Wear of polyethylene against oxidized zirconium femoral components. J Arthroplasty 2012;27:116–21. https://doi.org/10.1016/j.arth.2011.06.002.Search in Google Scholar PubMed

2. Sharkey, PF, Lichstein, PM, Shen, C, Tokarski, AT, Parvizi, J. Why are total knee arthroplasties failing today – has anything changed after 10 Years? J Arthroplasty 2014;29:1774–8. https://doi.org/10.1016/j.arth.2013.07.024.Search in Google Scholar PubMed

3. Sundfeldt, M, V Carlsson, L, B Johansson, C, Thomsen, P, Gretzer, C. Aseptic loosening, not only a question of wear: a review of different theories. Acta Orthop 2006;77:177–97. https://doi.org/10.1080/17453670610045902.Search in Google Scholar PubMed

4. Bahraminasab, M, Sahari, BB, Edwards, KL, Farahmand, F, Jahan, A, Hong, TS, et al.. On the influence of shape and material used for the femoral component pegs in knee prostheses for reducing the problem of aseptic loosening. Mater Des 2014;55:416–28. https://doi.org/10.1016/j.matdes.2013.10.020.Search in Google Scholar

5. Bae, DK, Song, SJ, Park, MJ, Eoh, JH, Song, JH, Park, CH. Twenty-year survival analysis in total knee arthroplasty by a single surgeon. J Arthroplasty 2012;27:1297–304.e1. https://doi.org/10.1016/j.arth.2011.10.027.Search in Google Scholar PubMed

6. Harrysson, OL, Hosni, YA, Nayfeh, JF. Custom-designed orthopedic implants evaluated using finite element analysis of patient-specific computed tomography data: femoral-component case study. BMC Muscoskel Disord 2007;8:91. https://doi.org/10.1186/1471-2474-8-91.Search in Google Scholar PubMed PubMed Central

7. Larsen, B, Jacofsky, MC, Jacofsky, DJ. Quantitative, comparative assessment of gait between single-radius and multi-radius total knee arthroplasty designs. J Arthroplasty 2015;30:1062–7. https://doi.org/10.1016/j.arth.2015.01.014.Search in Google Scholar PubMed

8. Minoda, Y, Kobayashi, A, Ikebuchi, M, Iwaki, H, Inori, F, Nakamura, H. Porous tantalum tibial component prevents periprosthetic loss of bone mineral density after total knee arthroplasty for five years – a matched cohort study. J Arthroplasty 2013;28:1760–4. https://doi.org/10.1016/j.arth.2013.03.031.Search in Google Scholar PubMed

9. Bergschmidt, P, Bader, R, Mittelmeier, W. Metal hypersensitivity in total knee arthroplasty: revision surgery using a ceramic femoral component–a case report. Knee 2012;19:144–7. https://doi.org/10.1016/j.knee.2011.01.001.Search in Google Scholar PubMed

10. Bhimji, S, Meneghini, RM. Micromotion of cementless tibial baseplates: keels with adjuvant pegs offer more stability than pegs alone. J Arthroplasty 2014;29:1503–6. https://doi.org/10.1016/j.arth.2014.02.016.Search in Google Scholar PubMed

11. Hutt, JRB, LeBlanc, M-A, Massé, V, Lavigne, M, Vendittoli, P-A. Kinematic TKA using navigation: surgical technique and initial results. Orthop Trauma Surg Res 2016;102:99–104. https://doi.org/10.1016/j.otsr.2015.11.010.Search in Google Scholar PubMed

12. Theodore, W, Twiggs, J, Kolos, E, Roe, J, Fritsch, B, Dickison, D, et al.. Variability in static alignment and kinematics for kinematically aligned TKA. Knee 2017;24:733–44. https://doi.org/10.1016/j.knee.2017.04.002.Search in Google Scholar PubMed

13. Maciąg, BM, Stolarczyk, A, Maciąg, GJ, Dorocińska, M, Stępiński, P, Szymczak, J, et al.. Does the anatomic design of total knee prosthesis allow for a better component fit than its nonanatomic predecessor? A matched cohort study. Arthroplasty Today 2021;12:62–7. https://doi.org/10.1016/j.artd.2021.09.001.Search in Google Scholar PubMed PubMed Central

14. Bugbee, WD, Mizu-uchi, H, Patil, S, D’Lima, D. Accuracy of implant placement utilizing customized patient instrumentation in total knee arthroplasty. Adv Orthop 2013;2013:1–6. https://doi.org/10.1155/2013/891210.Search in Google Scholar PubMed PubMed Central

15. Steinbrück, A, Schröder, C, Woiczinski, M, Fottner, A, Pinskerova, V, Müller, PE, et al.. Femorotibial kinematics and load patterns after total knee arthroplasty: an in vitro comparison of posterior-stabilized versus medial-stabilized design. Clin Biomech 2016;33:42–8. https://doi.org/10.1016/j.clinbiomech.2016.02.002.Search in Google Scholar PubMed

16. Scuderi, GR, Tria, AJ. Knee arthroplasty handbook, 1st ed. New York: Springer-Verlag; 2005.10.1007/0-387-33531-5_1Search in Google Scholar

17. Yang, B, Yu, J-K, Zheng, Z-Z, Lu, Z-H, Zhang, J-Y, Cheng, J-H. Computed tomography morphometric study of gender differences in osteoarthritis proximal tibias. J Arthroplasty 2013;28:1117–20. https://doi.org/10.1016/j.arth.2012.07.036.Search in Google Scholar PubMed

18. Meneghini, RM, de Beaubien, BC. Early failure of cementless porous tantalum monoblock tibial components. J Arthroplasty 2013;28:1505–8. https://doi.org/10.1016/j.arth.2013.03.005.Search in Google Scholar PubMed

19. Dupraz, I, Bollinger, A, Deckx, J, Schierjott, RA, Utz, M, Jacobs, M. Using statistical shape models to optimize TKA implant design. Appl Sci Multi Digit Publish Inst 2022;12:1020 https://doi.org/10.3390/app12031020.Search in Google Scholar

20. Bah, MT, Shi, J, Heller, MO, Suchier, Y, Lefebvre, F, Young, P, et al.. Inter-subject variability effects on the primary stability of a short cementless femoral stem. J Biomech 2015;48:1032–42. https://doi.org/10.1016/j.jbiomech.2015.01.037.Search in Google Scholar PubMed

21. Bali, K, Walker, P, Bruce, W. Custom-fit total knee arthroplasty: our initial experience in 32 knees. J Arthroplasty 2012;27:1149–54. https://doi.org/10.1016/j.arth.2011.12.006.Search in Google Scholar PubMed

22. White, PB, Ranawat, AS. Patient-specific total knees demonstrate a higher manipulation rate compared to “off-the-shelf implants.” J Arthroplasty 2016;31:107–11. https://doi.org/10.1016/j.arth.2015.07.041.Search in Google Scholar PubMed

23. Bahraminasab, M, Sahari, BB, Edwards, KL, Farahmand, F, Hong, TS, Arumugam, M, et al.. Multi-objective design optimization of functionally graded material for the femoral component of a total knee replacement. Mater Des 2014;53:159–73. https://doi.org/10.1016/j.matdes.2013.06.050.Search in Google Scholar

24. Enab, TA, Bondok, NE. Material selection in the design of the tibia tray component of cemented artificial knee using finite element method. Mater Des 2013;44:454–60. https://doi.org/10.1016/j.matdes.2012.08.017.Search in Google Scholar

25. van den Heever, DJ, Scheffer, C, Erasmus, P, Dillon, E. Contact stresses in a patient-specific unicompartmental knee replacement. Clin Biomech 2011;26:159–66. https://doi.org/10.1016/j.clinbiomech.2010.09.007.Search in Google Scholar PubMed

26. Dopico-González, C, New, AM, Browne, M. Probabilistic finite element analysis of the uncemented hip replacement – effect of femur characteristics and implant design geometry. J Biomech 2010;43:512–20. https://doi.org/10.1016/j.jbiomech.2009.09.039.Search in Google Scholar PubMed

27. Easley, SK, Pal, S, Tomaszewski, PR, Petrella, AJ, Rullkoetter, PJ, Laz, PJ. Finite element-based probabilistic analysis tool for orthopaedic applications. Comput Progr Biomed 2007;85:32–40. https://doi.org/10.1016/j.cmpb.2006.09.013.Search in Google Scholar PubMed

28. Chua, M, Chui, C-K. Probabilistic predictive modelling of carbon nanocomposites for medical implants design. J Mech Behav Biomed Mater 2015;44:164–72. https://doi.org/10.1016/j.jmbbm.2015.01.013.Search in Google Scholar PubMed

29. Bah, MT, Shi, J, Browne, M, Suchier, Y, Lefebvre, F, Young, P, et al.. Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model. Med Eng Phys 2015;37:995–1007. https://doi.org/10.1016/j.medengphy.2015.08.004.Search in Google Scholar PubMed

30. Luo, Q, Nakade, R, Dong, X, Rong, Q, Wang, X. Effect of mineral–collagen interfacial behavior on the microdamage progression in bone using a probabilistic cohesive finite element model. J Mech Behav Biomed Mater 2011;4:943–52. https://doi.org/10.1016/j.jmbbm.2011.02.003.Search in Google Scholar PubMed

31. Rohlmann, A, Nabil Boustani, H, Bergmann, G, Zander, T. Effect of a pedicle-screw-based motion preservation system on lumbar spine biomechanics: a probabilistic finite element study with subsequent sensitivity analysis. J Biomech 2010;43:2963–9. https://doi.org/10.1016/j.jbiomech.2010.07.018.Search in Google Scholar PubMed

32. Hoey, D, Taylor, D. Quantitative analysis of the effect of porosity on the fatigue strength of bone cement. Acta Biomater 2009;5:719–26. https://doi.org/10.1016/j.actbio.2008.08.024.Search in Google Scholar PubMed

33. Mangado, N, Piella, G, Noailly, J, Pons-Prats, J, Ballester, MÁG. Analysis of uncertainty and variability in finite element computational models for biomedical engineering: characterization and propagation. Front Bioeng Biotechnol 2016;4–85. https://doi.org/10.3389/fbioe.2016.00085.10.3389/fbioe.2016.00085Search in Google Scholar PubMed PubMed Central

34. Saleh, MM, El-Kalla, IL, Ehab, MM. Stochastic finite element technique for stochastic one-dimension time-dependent differential equations with random coefficients. Differ Eq Nonlinear Mech Hindawi 2007:e48527. https://doi.org/10.1155/2007/48527.Search in Google Scholar

35. Nouy, A, Clément, A, Schoefs, F, Moës, N. An extended stochastic finite element method for solving stochastic partial differential equations on random domains. Comp Met Applied Mech Eng 2008;197:4663–82. https://doi.org/10.1016/j.cma.2008.06.010.Search in Google Scholar

36. Hua, XG, Ni, YQ, Chen, ZQ, Ko, JM. An improved perturbation method for stochastic finite element model updating. Int J Num Met Eng 2008;73:1845–64. https://doi.org/10.1002/nme.2151.Search in Google Scholar

37. Navacchia, A, Myers, CA, Rullkoetter, PJ, Shelburne, KB. Prediction of in vivo knee joint loads using a global probabilistic analysis. J Biomech Eng 2016;138:031002. https://doi.org/10.1115/1.4032379.Search in Google Scholar PubMed PubMed Central

38. Kaymaz, I, Bayrak, O, Karsan, O, Celik, A, Alsaran, A. Failure analysis of the cement mantle in total hip arthroplasty with an efficient probabilistic method. Proc Inst Mech Eng H 2014;228:409–17. https://doi.org/10.1177/0954411914529428.Search in Google Scholar PubMed

39. Wille, H, Ruess, M, Rank, E, Yosibash, Z. Uncertainty quantification for personalized analyses of human proximal femurs. J Biomech 2016;49:520–7. https://doi.org/10.1016/j.jbiomech.2015.11.013.Search in Google Scholar PubMed

40. Korkmaz, IH, Kaymaz, İ, Yildirim, ÖS. A new design for maximum conformity of total knee prosthesis to femur and tibia. J Long Term Eff Med Implants 2016;26:365–74. https://doi.org/10.1615/jlongtermeffmedimplants.2017020207.Search in Google Scholar PubMed

41. Villa, T, Migliavacca, F, Gastaldi, D, Colombo, M, Pietrabissa, R. Contact stresses and fatigue life in a knee prosthesis: comparison between in vitro measurements and computational simulations. J Biomech 2004;37:45–53. https://doi.org/10.1016/s0021-9290(03)00255-0.Search in Google Scholar

42. Completo, A, Rego, A, Fonseca, F, Ramos, A, Relvas, C, Simões, JA. Biomechanical evaluation of proximal tibia behaviour with the use of femoral stems in revision TKA: an in vitro and finite element analysis. Clin Biomech 2010;25:159–65. https://doi.org/10.1016/j.clinbiomech.2009.10.011.Search in Google Scholar PubMed

43. Kaymaz, I, McMahon, CA. A response surface method based on weighted regression for structural reliability analysis. Probabilist Eng Mech 2005;20:11–7. https://doi.org/10.1016/j.probengmech.2004.05.005.Search in Google Scholar

44. Zhang, J-Y, Wang, J, Tian, D-M, Jiang, D-P, Li, J-J, Hu, Y-C. Spherical center and rotating platform hinged knee prosthesis: finite-element model establishment, verification and contact analysis. Knee 2020;27:731–9. https://doi.org/10.1016/j.knee.2020.04.022.Search in Google Scholar PubMed

45. Kayabasi, O, Ekici, B. Probabilistic design of a newly designed cemented hip prosthesis using finite element method. Mater Des 2008;29:963–71. https://doi.org/10.1016/j.matdes.2007.03.024.Search in Google Scholar

46. Nicolella, DP, Thacker, BH, Katoozian, H, Davy, DT. The effect of three-dimensional shape optimization on the probabilistic response of a cemented femoral hip prosthesis. J Biomech 2006;39:1265–78. https://doi.org/10.1016/j.jbiomech.2005.03.010.Search in Google Scholar PubMed

47. Zaribaf, FP. Medical-grade ultra-high molecular weight polyethylene: past, current and future. Mater Sci Tech 2018;34:1940–53. https://doi.org/10.1080/02670836.2018.1469455.Search in Google Scholar

48. Rocha, M, Mansur, A, Mansur, H. Characterization and accelerated ageing of UHMWPE used in orthopedic prosthesis by peroxide. Materials 2009;2:562–76. https://doi.org/10.3390/ma2020562.Search in Google Scholar

49. Kaklamani, G, Mehrban, N, Chen, J, Bowen, J, Dong, H, Grover, L, et al.. Effect of plasma surface modification on the biocompatibility of UHMWPE. Biomed Mater 2010;5:054102. https://doi.org/10.1088/1748-6041/5/5/054102.Search in Google Scholar PubMed

50. Doucet, N, Lame, O, Vigier, G, Dore, F, Seguela, R. Sintering kinetics of UHMWPE nascent powders by high velocity compaction: influence of molecular weight. Eur Polym J 2013;49:1654–61. https://doi.org/10.1016/j.eurpolymj.2013.02.028.Search in Google Scholar

51. Zheng, N, Fleisig, GS, Escamilla, RF, Barrentine, SW. An analytical model of the knee for estimation of internal forces during exercise. J Biomech 1998;31:963–7. https://doi.org/10.1016/s0021-9290(98)00056-6.Search in Google Scholar

52. Sharma, A, Leszko, F, Komistek, RD, Scuderi, GR, Cates, HE, Liu, F. In vivo patellofemoral forces in high flexion total knee arthroplasty. J Biomech 2008;41:642–8. https://doi.org/10.1016/j.jbiomech.2007.09.027.Search in Google Scholar PubMed

53. Escamilla, RF, Zheng, N, MacLeod, TD, Edwards, WB, Hreljac, A, Fleisig, GS, et al.. Patellofemoral compressive force and stress during the forward and side lunges with and without a stride. Clin Biomech 2008;23:1026–37. https://doi.org/10.1016/j.clinbiomech.2008.05.002.Search in Google Scholar PubMed

54. Scott, WN, Insall, TJN. Surg knee. Philadelphia, PA: Elsevier; 2006.Search in Google Scholar

55. Gallo, J, Goodman, SB, Konttinen, YT, Wimmer, MA, Holinka, M. Osteolysis around total knee arthroplasty: a review of pathogenetic mechanisms. Acta Biomater 2013;9:8046–58. https://doi.org/10.1016/j.actbio.2013.05.005.Search in Google Scholar PubMed PubMed Central

56. Bahraminasab, M, Sahari, BB, Hassan, MR, Arumugam, M. Finite element analysis of the effect of shape memory alloy on the stress distribution and contact pressure in total knee replacement. Trends Biomater Artif Organs 2011;3:6.Search in Google Scholar

57. Lavernia, CJ, Rodriguez, JA, Iacobelli, DA, Hungerford, DS, Krackow, KA. Bone mineral density of the femur in autopsy retrieved total knee arthroplasties. J Arthroplasty 2014;29:1681–6. https://doi.org/10.1016/j.arth.2014.03.010.Search in Google Scholar PubMed

Received: 2021-05-03
Accepted: 2022-03-30
Published Online: 2022-05-09
Published in Print: 2022-08-26

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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  2. Research Articles
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  7. Designing and in vitro testing of a novel patient-specific total knee prosthesis using the probabilistic approach
  8. Biomechanical comparison of different prosthetic materials and posterior implant angles in all-on-4 treatment concept by three-dimensional finite element analysis
  9. Non-woven textiles for medical implants: mechanical performances improvement
  10. Corrigendum
  11. Corrigendum to: Developing a novel resorptive hydroxyapatite-based bone substitute for over-critical size defect reconstruction: physicochemical and biological characterization and proof of concept in segmental rabbit’s ulna reconstruction
https://doi.org/10.1515/bmt-2021-0136
Keywords for this article
experimental validation; finite element analysis; probability-based design; total knee arthroplasty

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Fetal phonocardiogram signals denoising using improved complete ensemble (EMD) with adaptive noise and optimal thresholding of wavelet coefficients
  4. Layer recurrent neural network-based diagnosis of Parkinson’s disease using voice features
  5. Automatic sleep scoring with LSTM networks: impact of time granularity and input signals
  6. Computer-aided diagnosis system for retinal disorder classification using optical coherence tomography images
  7. Designing and in vitro testing of a novel patient-specific total knee prosthesis using the probabilistic approach
  8. Biomechanical comparison of different prosthetic materials and posterior implant angles in all-on-4 treatment concept by three-dimensional finite element analysis
  9. Non-woven textiles for medical implants: mechanical performances improvement
  10. Corrigendum
  11. Corrigendum to: Developing a novel resorptive hydroxyapatite-based bone substitute for over-critical size defect reconstruction: physicochemical and biological characterization and proof of concept in segmental rabbit’s ulna reconstruction
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